--- title: 'Data Science at Topsort' canonical: 'https://feeny.ai/job/data-science-topsort-santiago-santiago-metropolitan-region-wgg9sx6r1kk8' type: 'job' last_seen: '2026-10-21' --- # Data Science at Topsort - **Company:** Topsort - **Location:** Santiago Santiago Metropolitan Region, Chile - **Posted:** 2026-10-20 - **Last confirmed live:** 2026-10-21 - **Apply:** https://job-boards.greenhouse.io/topsort/jobs/5458904008 ## Job description We're quickly growing and super excited for you to join us! ## About Topsort Topsort is a global Commerce AI company making advanced advertising and AI-powered technology accessible to businesses of all sizes. Our technology helps retailers and marketplaces grow through smarter advertising, real-time auctions, and intelligent product discovery. With a presence in 40+ countries and a growing international team, we're building the technology behind the next generation of commerce. What Is This Role Like? We're hiring a Data Scientist to help improve how Topsort ranks and retrieves products for search and ads, predicts user behavior, and supports advertiser planning through reliable predictive models. You'll work closely with Product and Engineering to turn complex data into actionable models and insights that drive better decisions and continuously improve our platform. ## What You'll Own - Forecasting Models: Develop and refine models for budget planning and advertiser spend, using time-series methods, regression, and machine learning. - Retrieval: Build and improve the models that select which products are candidates to be shown for each search or placement. - Ranking: Develop and iterate on rankers and re-rankers that combine relevance, CTR/CVR predictions and business constraints for organic and sponsored placements. - Query & Product Understanding: Improve how we represent queries and products, including multilingual catalogs, sparse or noisy metadata, and new products with no interaction history (cold start). - Data Analysis: Explore large datasets to identify trends, assess data quality, and uncover opportunities to improve predictions. - Production Delivery: Ship models into our ad engine and serving stack, and build the training and evaluation pipelines on large-scale event data. - Cross-Functional Delivery: Partner with Product and Engineering to integrate models into platform workflows and translate findings into actionable recommendations. What Success Looks Like - Reliable Predictions: Models demonstrate consistent performance against defined baselines, offline and in live experiments, with uncertainty and limitations clearly understood. - Better Relevance: Ranking and retrieval improvements produce measurable lift for shoppers and advertisers. - Better Planning: Budget and advertiser spend forecasts provide useful inputs for planning and decision-making. - Practical Adoption: Product and Engineering teams can use model outputs effectively in the platform and relevant workflows. - Continuous Improvement: Model errors, experiment results and changing data patterns lead to clear, evidence-based improvements. ## What You'll Bring Don't check every box? We'd still love to hear from you. We value curiosity, strong judgment, and people who take ownership of results: - Relevant Experience: 5+ years of experience in data science, with a strong focus on forecasting. - Academic Background: A Ph.D. in Data Science, Statistics, Mathematics, or a related quantitative field. - Ranking & Retrieval: Direct experience building search, recommendation or ads ranking systems in production. - Deep Learning: Hands-on experience with PyTorch or similar, including training embedding-based retrieval or ranking models. - Python & SQL: Strong Python and SQL; comfortable building datasets from raw event logs at scale. - Experimentation: Solid statistics fundamentals and experience designing and reading A/B tests. - Shipping Mindset: Comfort with AI-assisted development tools and a bias toward getting models into production. Nice To Have: - Retail media / AdTech experience, auction or bidding systems. - LLM-based retrieval, model distillation, approximate nearest neighbor search (HNSW, FAISS). - Learning-to-rank at scale, or multi-objective ranking. Who Thrives Here We set a high bar for engineering because the systems we build matter. You'll thrive here if you: - Ownership & Quality: You take responsibility for what you build, write production-ready code, and leave systems better than you found them. - Engineering Judgment: You make thoughtful technical decisions, communicate tradeoffs honestly, and balance speed with long-term reliability. - Collaboration & Communication: You share knowledge, communicate openly, and work effectively across teams to solve complex challenges. - Curiosity & Attention to Detail: You care about the details, continuously improve your skills, and explore new technologies with a critical mindset. We are proud to be an equal opportunity employer and to foster a workplace where diversity is valued and celebrated. We believe that diverse perspectives and experiences strengthen our teams and drive better outcomes. We respect and value any race, religion, color, national origin, ancestry, caste, gender, gender identity or expression, sexual orientation, age, disability, medical condition, pregnancy, genetic information, marital status, or military service. Do you sound like the right fit? Let's dive right in! ## About Topsort ## Company Overview - **One-liner**: Topsort provides AI-powered, privacy-first retail media infrastructure that enables marketplaces, retailers, and commerce platforms to launch and scale monetization through real-time auctions, sponsored listings, display, offsite, and in-store advertising. - **Entity Type**: Private (Series A, post-money valuation $150M as of March 2024) - **Headquarters**: Palo Alto, California, United States - **Founded**: 2021 - **Founders**: Not publicly available (company spokesperson identified as "Ye" in media) ## Core Business - **Primary industry/industries**: Retail media infrastructure, ad tech, commerce monetization, AI-powered advertising - **Target customers**: B2B – marketplaces, retailers, delivery apps, travel platforms, and commerce networks (both enterprise and SMB) - **Mission or purpose statement**: "Make world-class monetization accessible to everyone" by bringing the same auction and AI-driven advertising infrastructure used by the largest marketplaces to every commerce platform. ## Products & Services - **T-Engine (Auction & Ranking Engine)**: High-performance, edge-deployed auction infrastructure for large-scale commerce media – sub-5ms p99 latency, 99.99% uptime SLA. - **Toptimize (AI Optimization Layer)**: Improves yield, pacing, ROAS, and relevance on top of existing ad stacks. - **T-Brain (Commerce Intelligence)**: Uses catalog, auction, campaign, and performance data to power smarter monetization and ranking. - **Data Genie (Retail Media Analytics)**: Unifies reporting, insights, benchmarking, and performance analysis. - **Tomi (AI Ad Ops Agent)**: Conversational AI agent for launching and managing retail media campaigns. - **Sponsored Listings**: Auction-based product promotion in search, category, and discovery surfaces. - **Sponsored Brands**: Brand-level advertising across commerce surfaces. - **Display & Banners**: Programmatic display advertising. - **In-Store Media**: Extends retail media into physical store environments. - **Sponsored Prompts**: Agentic ad formats for AI-native commerce (e.g., within conversational shopping experiences). - **BIDLESS™**: Autobidding technology for automated campaign optimization. ## Market Standing - **Valuation/Market Cap**: $150 million post-money (Series A, March 2024); previously $110 million post-money (seed round, 2022) - **Key Metric**: Total funding raised – $28.6 million ($8M seed in 2022, $20M Series A in 2024) - **Notable Investors/Partners**: Upload Ventures (lead Series A), Quiet Capital, Pear Ventures - **Growth Signals**: 120+ employees across 4 continents; 40+ countries served; billions of commerce decisions processed; <5ms auction latency; 99.99% uptime; expanded into offsite and in-store media in 2023–2025; launched new ad formats (Sponsored Brands, Video Ads, Sponsored Prompts) and AI agents (Tomi, Data Genie). ## Competitive Advantages - **Privacy-first approach**: Built for a post-cookie world with a Cleanroom feature that combines data without compromising user privacy. - **AI-native infrastructure**: Auctions, relevance, measurement, and optimization are designed for AI-driven commerce (including agentic shopping). - **Omnichannel coverage**: Supports search, category, display, offsite, in-store, and emerging AI prompt surfaces from a single API. - **Low latency at global scale**: Edge-deployed auction engine with sub-5ms p99 latency across nine regions. - **Accessibility**: Democratizes advanced monetization technology previously limited to giants like Amazon, making it available to smaller marketplaces and retailers. ## Strategic Focus - **AI-native commerce**: Expanding monetization formats for agentic and conversational shopping experiences (e.g., Sponsored Prompts). - **Global expansion**: Growing presence across North America, Europe, Asia Pacific, and Latin America. - **Product breadth**: Continuing to add ad formats (video, in-store, offsite) and AI-powered automation (Tomi, Data Genie, Toptimize). - **Post-cookie leadership**: Positioning as the clean, privacy-compliant alternative for retail media. ## Why Work Here - **Culture**: Described as "smart, driven, and from all over the globe" – a team building infrastructure that powers the next generation of commerce. - **Engineering focus**: Engineers work on high-scale auction systems, AI/ML optimization, distributed systems, and real-time data pipelines. - **Global team**: Offices in Palo Alto (HQ), Munich, Melbourne, Santiago, and Barcelona; remote-friendly culture implied by distributed team. - **Growth trajectory**: Fast-growing startup (Series A, 120+ employees) with a clear product-market fit in a hot sector (retail media). - **Impact**: Opportunity to build the underlying monetization infrastructure for hundreds of commerce platforms, processing billions of decisions. ## Sources 1. [Topsort Website](https://www.topsort.com/) 2. [Topsort About Page](https://www.topsort.com/about) 3. [Topsort Careers (Greenhouse)](https://job-boards.greenhouse.io/topsort) 4. [Topsort LinkedIn](https://www.linkedin.com/company/topsort) 5. [TechCrunch: "Topsort helps e-commerce create ads without being ‘creepy’"](https://techcrunch.com/2024/03/04/topsort-150m-e-commerce-ads/) ## Other roles at Topsort - [Paralegal](https://feeny.ai/job/paralegal-topsort-somerville-5rpk0tv254kr) — Somerville, MA - [Application for Engineering Roles](https://feeny.ai/job/application-for-engineering-roles-topsort-santiago-santiago-metropolitan-region-p10rjkcj9z69) — Santiago Santiago Metropolitan Region, Chile - [Software Engineer, Infrastructure](https://feeny.ai/job/software-engineer-infrastructure-topsort-santiago-santiago-metropolitan-region-3npfnfbvk1wv) — Santiago Santiago Metropolitan Region, Chile - [Data Science](https://feeny.ai/job/data-science-axle-energy-london-vfysvb1pesqe) — London, United Kingdom